Data Scientist II

This is a hybrid role, and the successful candidate will collaborate with internal business partners to implement data-driven solutions with measurable business value. The candidate must have experience working within a team environment as well as independently, on multiple projects simultaneously, and work well within deadlines. The candidate must have experience designing, conducting, and interpreting statistical analyses using common statistical software tools (e.g., R, Python, etc.) and techniques (e.g., linear and logistic modeling, tree-based modeling, neural nets, anomaly detection, image/video classification, principal component analysis (PCA), etc.) Experience with Python for big-data analysis built upon structured (SQL) and unstructured (data lakes / Hadoop) file systems is a plus. Preference will be given to candidates with experience in time series analysis prediction with statistics and machine learning. Proficiency in report generation, query writing, databases, and data visualization is imperative and proven / demonstrable experience in this regard is mandatory.

KEY RESPONSIBILITIES:

• Develop and deploy predictive and prescriptive analytic solutions in Python to drive business value
• Develop algorithms, methods, and tools to ingest large data sets to predict outcomes. Generate semiautomated and automated decision systems in manufacturing and in the manufacturing supporting organizations.
• Provide clear direction to data engineers for model specific data transformation requirements
• Generate descriptive visualizations and presentations to communicate insights.
• Process, cleanse, and verify the integrity of data used for analysis
• Perform rapid ad-hoc analysis and present results in a clear manner starting with structured or unstructured datasets
• Communicate clearly advanced concepts and information to varied audiences
• Maintain an up-to-date knowledge of technology trends

MINIMUM EDUCATION, KNOWLEDGE, SKILLS AND ABILITIES:

• Bachelor's degree in data science, Engineering, Computer Science, Information Systems or related discipline with equivalent work experience in data analysis in lieu of an advanced degree.
• Proven expertise in leveraging statistics, machine learning, algorithms and advanced mathematics to solve engineering problems.
• Two plus years of hands-on experience in data science, or similar experience in mining, steel making, or related industry.
• Working knowledge of statistics and programming involving time-series data.
• Demonstrated skill in the use of one or more analytic, visualization and data querying software tools or languages (e.g., R, Python, Java, Tableau, SQL, Hive / Hadoop).
• Demonstrated skill at data cleansing, data quality assessment, and using analytics for data assessment.
• Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets.
• Demonstrated skill at data visualization and storytelling for an audience of stakeholders.
• Ability to work independently.
• Strong organizational, project, process and time management skills.
• Excellent communication skills.
• Ability to think creatively and solve problems.

Work Environment/Physical Requirements:

• Commuter remote structure.
• Ability to travel 15-20% of the time.
• Must be able to constantly operate a computer.
• Must be able to remain stationary 50% of the time.

Salary Range: $88,762 - $110,000/yr. This base salary range is a good faith estimate. Based on candidate skills/experience the final offer may be lower/higher.

Salary : $88,762 - $110,000